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CNTK v.2.0 Beta 4 Release Notes

This is a summary of new features delivered with the Beta 4 release of CNTK V.2.0.

ASGD/Hogwild! training using Microsoft’s Parameter Server (Project Multiverso)

This release introduces Asynchronous Stochastic Gradient Descent (ASGD)/Hogwild! training parallelization support using Microsoft’s Parameter Server (Project Multiverso).

CNTK Python API. Distributed Scenarios support

This release add the support of Distributed scenarios. See more in the sections on Distributed scenarios in ConvNet and ResNet examples. (All examples are also available as a part of CNTK Binary Packages)

Memory compression

This release introduces a Memory Compression, an ability to trade off memory usage with compute. See how to enable the feature in Top level configurations Wiki article (hyperCompressMemory variable).

Reorganizing location of Examples and Tutorials

We continue re-organizing and re-arranging CNTK Examples and Tutorials. Please, be aware that as a part of the process we are gradually removing outdated Python examples.

CNTK Docker image with 1bit-SGD support

You may now compile and install CNTK with 1bit-SGD support as a Docker container. Thus all three CNTK configurations may be implemented as Docker containers. See more on CNTK Docker containers here.

CNTK Evaluation library

Please note that in this release there will be NO update of CNTK NuGet package. The latest package is available in CNTK V.2.0 Beta 3.

Stability Improvements

We continue fine tuning new features and fixing different bugs - thank you once again for the constant feedback. You are not required to adopt your code or models to take an advantage of these improvements.

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